OPTIMIZATION OF REFLUX EXTRACTION FOR CAESALPINIA SAPPAN LINN. WOOD BY USING RESPONSE SURFACE METHODOLOGY

Authors

  • Mohd Azahar Mohd Ariff Faculty of Chemical Engineering, Universiti Teknologi MARA (UiTM) Cawangan Pulau Pinang, 13500 Permatang Pauh, Pulau Pinang, MALAYSIA https://orcid.org/0000-0003-1777-6457
  • Muhammad Syafiq Abd Jalil Faculty of Chemical Engineering, Universiti Teknologi MARA (UiTM) Cawangan Pulau Pinang, 13500 Permatang Pauh, Pulau Pinang, MALAYSIA
  • Noor ‘Aina Abdul Razak Faculty of Computer Science and Mathematics, Universiti Teknologi MARA, Cawangan Pulau Pinang, 13500 Permatang Pauh, Pulau Pinang, MALAYSIA
  • Jefri Jaapar Faculty of Chemical Engineering, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, MALAYSIA

DOI:

https://doi.org/10.11113/jurnalteknologi.v83.14590

Keywords:

Caesalpinia Sappan Linn., Responce Surface Methodology, Reflux extraction, UV-vis spectrophotometer, Optimization

Abstract

Caesalpinia sappan linn. (CSL) is a plant which is also known as Sepang tree contains various medicinal values such as to treat diarrhea, skin rashes, syphilis, jaundice, drinking water for blood purifying, diabetes, and to improve skin complexion. The aim of this study is to obtain the most optimum condition in terms of the ratio of sample to solvent, particle size, and extraction time to get the highest amount of concentration of the CSL extract. In this study, the ranges of each parameters used were: ratio sample to solvent: 1.0:20, 1.5:20, 2.0:20, 2.5:20, 3.0:20, particle size: 1 mm, 500 um, 250 um, 125 um, 63 um, and extraction time: 1 hr, 2 hr, 3 hr, 4 hr, 5 hr. The concentration was analyzed using a UV-vis spectrophotometer. The optimum conditions were obtained by response surface methodology. From the design, 20 samples were run throughout this experiment. The optimized value from the RSM were 2.0:20 for ratio sample to solvent, 125 µm of particle size and 2.48 hours with the concentration of 37.1184 ppm. The accuracy of the predictive model was validated with 2 repeated runs and the mean percentage error was less than 3%. This confirmed the model’s capability for optimizing the conditions for the reflux extraction of CSL’s wood.

Author Biography

  • Mohd Azahar Mohd Ariff, Faculty of Chemical Engineering, Universiti Teknologi MARA (UiTM) Cawangan Pulau Pinang, 13500 Permatang Pauh, Pulau Pinang, MALAYSIA

    Molecular System Design, Process & Optimization Research Group (MODEPRO), Universiti Teknologi MARA (UiTM) Cawangan Pulau Pinang, 13500 Permatang Pauh, Pulau Pinang, MALAYSIA

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Published

2020-12-07

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Section

Science and Engineering

How to Cite

OPTIMIZATION OF REFLUX EXTRACTION FOR CAESALPINIA SAPPAN LINN. WOOD BY USING RESPONSE SURFACE METHODOLOGY. (2020). Jurnal Teknologi, 83(1), 85-92. https://doi.org/10.11113/jurnalteknologi.v83.14590